MobileCoach

The vision of the MobileCoach team is to provide an open source behavioral intervention platform for fully-automated digital interventions. Due to a modular and extendable structure as well as an architecture rooted in the logics and legal claims of open-source software, the MobileCoach lays a fruitful ground for digital interventions in several application domains of behavior change. For example, the MobileCoach can be used to design and evaluate digital health interventions in the context of smoking cessation, nutrition or physical activity.

Based on personal characteristics and prior behavior assessed when participating in a digital intervention, the MobileCoach uses communication services (e.g. SMS) or sensor services (e.g. physical activity tracker) to monitor central indicators of the particular behavior on a regular basis. Building on individual data, MobileCoach users profit from individualized messages and valuable insights motivating for long-term behavior change.

An overview of a typical MobileCoach intervention is shown in Figure “A typical MobileCoach intervention” below. Following the registration process and an initial behavioral assessment at T0, the target behavior is monitored and according to it, participants receive a tailored intervention with individual feedback and recommendations until T1, for example, three to 12 months after T0. The long-term target behavior is finally evaluated in a follow-up assessment at T2, for example, three months after T1. This long-term target behavior is used as primary outcome variable to test the efficacy of the underlying MobileCoach intervention.

An overview of the various web based and SMS based user interfaces for participants of MobileCoach interventions is shown in Figure “The MobileCoach for participants” below. With the exception of the SMS based user interface, content and layout elements are fully customizable such that the target behavior can be supported as effective and efficient as possible. Native MobileCoach applications for mobile devices, desktop computers or ubiquitous computing environments will be made available as part of upcoming MobileCoach interventions and projects.

Domain experts such as physicians, psychologists or, more generally, behavioral intervention experts can use a lightweight web application to design and evaluate MobileCoach interventions. That is, no technical programming skills are required to design the baseline assessment, the tailored web-based feedback, the intervention rules or content elements. Some screenshots of the web application are shown in Figure “The MobileCoach for Domain Experts” below. Domain experts are also able to import and export interventions. This also includes an export of intervention data in the CSV format that allows further data processing and analyses with statistical packages such as R, Matlab or SPSS. However, real-time monitoring and longitudinal data analyses will be integrated directly in the MobileCoach web application in upcoming projects.

In the pilot phase, the MobileCoach will support two concrete health behaviors related to the public health context. For more information on these interventions, please go to the section Projects and read about our first projects MobileCoach Tobacco and MobileCoach Alcohol. Due to its open-source character, however, future research teams around the globe may contribute by adding features to the software and broadening the number of supported behaviors.

The first release of the open source MobileCoach platform can be downloaded in our section For Developers.

Features of the latest stable release (1.6.0 - DM10)

Last updated: August 7th, 2017

MESSAGES & INTERVENTION FLOW

Intervention rules are used to describe the flow of the intervention (e.g. when to send which messages):

Rules can send messages at specific points in time and define the time period in which an answer is expected

MobileCoach Tobacco: Efficacy Study, 2014-2016

Background: Tobacco smoking prevalence continues to be high, particularly among adolescents and young adults with lower educational levels, and is therefore a serious public health problem. Tobacco smoking and problem drinking often co-occur and relapses after successful smoking cessation are often associated with alcohol use. This study aims at testing the efficacy of the integrated smoking cessation and alcohol intervention MobileCoach Tobacco+ by comparing it to the smoking cessation only intervention MobileCoach Tobacco for young people, delivered via the Internet and mobile phone.

Methods/Design: A two-arm cluster-randomised controlled trial with one follow-up assessment after 6 months will be conducted. Participants in the integrated intervention group will: (1) receive individually tailored web-based feedback on their drinking behaviour based on age and gender norms, (2) receive individually tailored mobile phone text messages to promote drinking within low-risk limits over a 3-month period, (3) receive individually tailored mobile phone text messages to support smoking cessation for 3 months, and (4) be offered the option of registering for a more intensive program that provides strategies for smoking cessation centred around a self-defined quit date. Participants in the smoking cessation only intervention group will only receive components (3) and (4). Study participants will be 1350 students who smoke tobacco daily/occasionally, from vocational schools in Switzerland. Main outcome criteria are 7-day point prevalence smoking abstinence and cigarette consumption assessed at the 6-month follow up.

Discussion: This is the first study testing a fully automated intervention for smoking cessation that simultaneously addresses alcohol use and interrelations between tobacco and alcohol use. The integrated intervention can be easily implemented in various settings and could be used with large groups of young people in a cost-effective way.

MobileCoach Alcohol: Efficacy Study, 2014-2016

Background: Problem drinking, particularly risky single-occasion drinking is widespread among adolescents and young adults in most Western countries. Mobile phone text messaging allows a proactive and cost-effective delivery of short messages at any time and place and allows the delivery of individualised information at times when young people typically drink alcohol. The main objective of the project is to test the efficacy of a combined web- and text messaging-based Intervention, named MobileCoach Alcohol to reduce problem drinking in young people with heterogeneous educational level.

Methods/Design: A two-arm cluster-randomised controlled trial with one follow-up assessment after 6 months will be conducted to test the efficacy of the intervention in comparison to assessment only. The fully-automated intervention program will provide an online feedback based on the social norms approach as well as individually tailored mobile phone text messages to stimulate (1) positive outcome expectations to drink within low-risk limits, (2) self-efficacy to resist alcohol and (3) planning processes to translate intentions to resist alcohol into action. Program participants will receive up to two weekly text messages over a time period of 3 months. Study participants will be 934 students from approximately 93 upper secondary and vocational schools in Switzerland. Main outcome criterion will be risky single-occasion drinking in the past 30 days preceding the follow-up assessment.

Discussion: This is the first study testing the efficacy of a combined web- and text messaging-based intervention to reduce problem drinking in young people. Given that this intervention approach proves to be effective, it could be easily implemented in various settings, and it could reach large numbers of young people in a cost-effective way.

For Providers

Behavioral research teams all around the globe are invited to collaborate with the MobileCoach team or to simply download, setup and use their own instance of the MobileCoach platform. Moreover, healthcare providers or other companies interested in fully-automated behavioral interventions are also invited to contact the MobileCoach team for joint projects.

Academia

As of today, the following research institutes discuss, design, provide and/or evaluate MobileCoach interventions:

Companies & Public Institutions

The following companies or public institutions discuss, design, provide and/or evaluate MobileCoach interventions:

Corporate Health Solutions GmbH, Zurich, Switzerland

Dr. Rebecca BrauchliChairwoman of the management board

For Developers

License

The initiators of the MobileCoach were eager to make this platform freely available to academia, public institutions and industry with the overall goal to promote further development resulting in useful evidence-based behavioral interventions. In this regard, the MobileCoach team has chosen the Apache 2 open source license such that the MobileCoach can even be used in commercial applications without any legal hassles.

Building Blocks of MobileCoach Interventions

Building on the foundations of automata theory, the technical design of the MobileCoach system follows the concepts of a state machine that uses intervention rules for state transitions, which can be referred to as a fully automated expert system. Here, the state is an aggregate of all relevant attributes related to the intervention progress of a participant (e.g. the messages received or answers provided) whereas state transitions triggered by intervention rules lead to a change in these attributes and thus, to a state change.

In particular, each participant of the intervention group is assigned to a particular intervention state based on her answers during the baseline assessment. In response to this assessment, a web-based feedback is generated individually by the system for each participant. Then, depending on a participant’s regular feedback (e.g. via text messages or sensor data from internet of things services) during the subsequent months, intervention rules trigger state transitions and the tailoring of the follow-up communication. In particular, intervention rules are traversed on a regular basis (e.g. once a day) for each participant, and, as a result, update the state of the corresponding participant and start communication (e.g. via text messages) in the form of a question, a feedback or a recommendation.

With upcoming projects, tailoring of interventions and prediction of state transitions with the help of machine learning algorithms will be the primary research focus of the MobileCoach team. As a summary, the three building blocks of MobileCoach interventions are depicted in Figure “Building Blocks of MobileCoaching”.

Technical Architecture

The technical architecture of this rule-based state machine as shown in Figure “The MobileCoach Architecture” is derived from the model-view-controller design pattern. It consists therefore of…

a service layer, i.e. the primary controller that utilizes the Java programming language and the expression evaluator Javaluator for the evaluation of the intervention rules and, finally,

a persistence layer, i.e. the model based on the document database mongoDB and plain files for storing the intervention content including a detailed protocol of all incoming and outgoing communication.

Password protection and Secure Sockets Layer (SSL) encoding are used to ensure the privacy and safety of data transfer.

Filler, A., Haug, S. and Kowatsch, T. (2014). The MobileCoach – An Open Source Solution for Behavioral Change Interventions. Abstract presented at the 7th Scientific Meeting of The International Society for Research on Internet Interventions (ISRII), Valencia, Spain. PDFTechnical Focus

Filler, A., Haug, S. and Kowatsch, T. (2014). The MobileCoach – An Open Source Solution for Behavioral Change Interventions. Abstract presented at the 7th Scientific Meeting of The International Society for Research on Internet Interventions (ISRII), Valencia, Spain. PDFTechnical Focus

2012

Team

The MobileCoach is continuously improved by an interdisciplinary research team. Among the various disciplines, team members are particularly experts in computer science, psychology and the field of public health.

Center for Digital Health Interventions, Health-IS Lab

Andreas FillerResearch Associate at the Health-IS Lab, Main Developer of the MobileCoach

Prof. Dr. Elgar FleischChair and Research Director of the Center for Digital Health Interventions

Chair of Information Management at the Department of Management, Technology and Economics, ETH Zurich, and Chair of Operations Management at the Institute of Technology Management, University of St. Gallen

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